mirror of
https://github.com/moses-smt/mosesdecoder.git
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284 lines
8.4 KiB
C++
284 lines
8.4 KiB
C++
// $Id$
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/***********************************************************************
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Moses - factored phrase-based language decoder
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Copyright (C) 2006 University of Edinburgh
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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***********************************************************************/
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#include <algorithm>
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#include <set>
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#include <queue>
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#include "HypothesisStackNormal.h"
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#include "TypeDef.h"
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#include "Util.h"
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#include "StaticData.h"
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#include "Manager.h"
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using namespace std;
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namespace Moses
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{
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HypothesisStackNormal::HypothesisStackNormal(Manager& manager) :
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HypothesisStack(manager)
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{
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m_nBestIsEnabled = StaticData::Instance().IsNBestEnabled();
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m_bestScore = -std::numeric_limits<float>::infinity();
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m_worstScore = -std::numeric_limits<float>::infinity();
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}
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/** remove all hypotheses from the collection */
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void HypothesisStackNormal::RemoveAll()
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{
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while (m_hypos.begin() != m_hypos.end()) {
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Remove(m_hypos.begin());
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}
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}
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pair<HypothesisStackNormal::iterator, bool> HypothesisStackNormal::Add(Hypothesis *hypo)
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{
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std::pair<iterator, bool> ret = m_hypos.insert(hypo);
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if (ret.second) {
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// equiv hypo doesn't exists
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VERBOSE(3,"added hyp to stack");
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// Update best score, if this hypothesis is new best
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if (hypo->GetTotalScore() > m_bestScore) {
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VERBOSE(3,", best on stack");
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m_bestScore = hypo->GetTotalScore();
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// this may also affect the worst score
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if ( m_bestScore + m_beamWidth > m_worstScore )
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m_worstScore = m_bestScore + m_beamWidth;
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}
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// update best/worst score for stack diversity 1
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if ( m_minHypoStackDiversity == 1 &&
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hypo->GetTotalScore() > GetWorstScoreForBitmap( hypo->GetWordsBitmap() ) ) {
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SetWorstScoreForBitmap( hypo->GetWordsBitmap().GetID(), hypo->GetTotalScore() );
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}
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VERBOSE(3,", now size " << m_hypos.size());
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// prune only if stack is twice as big as needed (lazy pruning)
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size_t toleratedSize = 2*m_maxHypoStackSize-1;
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// add in room for stack diversity
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if (m_minHypoStackDiversity)
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toleratedSize += m_minHypoStackDiversity << StaticData::Instance().GetMaxDistortion();
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if (m_hypos.size() > toleratedSize) {
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PruneToSize(m_maxHypoStackSize);
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} else {
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VERBOSE(3,std::endl);
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}
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}
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return ret;
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}
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bool HypothesisStackNormal::AddPrune(Hypothesis *hypo)
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{
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// too bad for stack. don't bother adding hypo into collection
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if (!StaticData::Instance().GetDisableDiscarding() &&
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hypo->GetTotalScore() < m_worstScore
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&& ! ( m_minHypoStackDiversity > 0
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&& hypo->GetTotalScore() >= GetWorstScoreForBitmap( hypo->GetWordsBitmap() ) ) ) {
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m_manager.GetSentenceStats().AddDiscarded();
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VERBOSE(3,"discarded, too bad for stack" << std::endl);
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FREEHYPO(hypo);
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return false;
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}
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// over threshold, try to add to collection
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std::pair<iterator, bool> addRet = Add(hypo);
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if (addRet.second) {
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// nothing found. add to collection
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return true;
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}
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// equiv hypo exists, recombine with other hypo
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iterator &iterExisting = addRet.first;
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Hypothesis *hypoExisting = *iterExisting;
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CHECK(iterExisting != m_hypos.end());
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m_manager.GetSentenceStats().AddRecombination(*hypo, **iterExisting);
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// found existing hypo with same target ending.
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// keep the best 1
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if (hypo->GetTotalScore() > hypoExisting->GetTotalScore()) {
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// incoming hypo is better than the one we have
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VERBOSE(3,"better than matching hyp " << hypoExisting->GetId() << ", recombining, ");
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if (m_nBestIsEnabled) {
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hypo->AddArc(hypoExisting);
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Detach(iterExisting);
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} else {
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Remove(iterExisting);
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}
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bool added = Add(hypo).second;
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if (!added) {
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iterExisting = m_hypos.find(hypo);
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TRACE_ERR("Offending hypo = " << **iterExisting << endl);
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abort();
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}
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return false;
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} else {
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// already storing the best hypo. discard current hypo
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VERBOSE(3,"worse than matching hyp " << hypoExisting->GetId() << ", recombining" << std::endl)
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if (m_nBestIsEnabled) {
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hypoExisting->AddArc(hypo);
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} else {
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FREEHYPO(hypo);
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}
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return false;
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}
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}
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void HypothesisStackNormal::PruneToSize(size_t newSize)
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{
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if ( size() <= newSize ) return; // ok, if not over the limit
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// we need to store a temporary list of hypotheses
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vector< Hypothesis* > hypos = GetSortedListNOTCONST();
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bool* included = (bool*) malloc(sizeof(bool) * hypos.size());
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for(size_t i=0; i<hypos.size(); i++) included[i] = false;
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// clear out original set
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for( iterator iter = m_hypos.begin(); iter != m_hypos.end(); ) {
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iterator removeHyp = iter++;
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Detach(removeHyp);
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}
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// add best hyps for each coverage according to minStackDiversity
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if ( m_minHypoStackDiversity > 0 ) {
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map< WordsBitmapID, size_t > diversityCount;
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for(size_t i=0; i<hypos.size(); i++) {
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Hypothesis *hyp = hypos[i];
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WordsBitmapID coverage = hyp->GetWordsBitmap().GetID();;
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if (diversityCount.find( coverage ) == diversityCount.end())
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diversityCount[ coverage ] = 0;
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if (diversityCount[ coverage ] < m_minHypoStackDiversity) {
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m_hypos.insert( hyp );
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included[i] = true;
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diversityCount[ coverage ]++;
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if (diversityCount[ coverage ] == m_minHypoStackDiversity)
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SetWorstScoreForBitmap( coverage, hyp->GetTotalScore());
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}
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}
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}
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// only add more if stack not full after satisfying minStackDiversity
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if ( size() < newSize ) {
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// add best remaining hypotheses
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for(size_t i=0; i<hypos.size()
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&& size() < newSize
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&& hypos[i]->GetTotalScore() > m_bestScore+m_beamWidth; i++) {
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if (! included[i]) {
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m_hypos.insert( hypos[i] );
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included[i] = true;
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if (size() == newSize)
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m_worstScore = hypos[i]->GetTotalScore();
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}
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}
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}
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// delete hypotheses that have not been included
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for(size_t i=0; i<hypos.size(); i++) {
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if (! included[i]) {
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FREEHYPO( hypos[i] );
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m_manager.GetSentenceStats().AddPruning();
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}
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}
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free(included);
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// some reporting....
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VERBOSE(3,", pruned to size " << size() << endl);
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IFVERBOSE(3) {
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TRACE_ERR("stack now contains: ");
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for(iterator iter = m_hypos.begin(); iter != m_hypos.end(); iter++) {
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Hypothesis *hypo = *iter;
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TRACE_ERR( hypo->GetId() << " (" << hypo->GetTotalScore() << ") ");
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}
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TRACE_ERR( endl);
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}
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}
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const Hypothesis *HypothesisStackNormal::GetBestHypothesis() const
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{
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if (!m_hypos.empty()) {
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const_iterator iter = m_hypos.begin();
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Hypothesis *bestHypo = *iter;
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while (++iter != m_hypos.end()) {
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Hypothesis *hypo = *iter;
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if (hypo->GetTotalScore() > bestHypo->GetTotalScore())
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bestHypo = hypo;
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}
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return bestHypo;
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}
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return NULL;
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}
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vector<const Hypothesis*> HypothesisStackNormal::GetSortedList() const
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{
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vector<const Hypothesis*> ret;
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ret.reserve(m_hypos.size());
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std::copy(m_hypos.begin(), m_hypos.end(), std::inserter(ret, ret.end()));
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sort(ret.begin(), ret.end(), CompareHypothesisTotalScore());
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return ret;
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}
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vector<Hypothesis*> HypothesisStackNormal::GetSortedListNOTCONST()
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{
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vector<Hypothesis*> ret;
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ret.reserve(m_hypos.size());
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std::copy(m_hypos.begin(), m_hypos.end(), std::inserter(ret, ret.end()));
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sort(ret.begin(), ret.end(), CompareHypothesisTotalScore());
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return ret;
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}
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void HypothesisStackNormal::CleanupArcList()
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{
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// only necessary if n-best calculations are enabled
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if (!m_nBestIsEnabled) return;
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iterator iter;
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for (iter = m_hypos.begin() ; iter != m_hypos.end() ; ++iter) {
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Hypothesis *mainHypo = *iter;
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mainHypo->CleanupArcList();
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}
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}
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TO_STRING_BODY(HypothesisStackNormal);
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// friend
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std::ostream& operator<<(std::ostream& out, const HypothesisStackNormal& hypoColl)
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{
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HypothesisStackNormal::const_iterator iter;
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for (iter = hypoColl.begin() ; iter != hypoColl.end() ; ++iter) {
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const Hypothesis &hypo = **iter;
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out << hypo << endl;
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}
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return out;
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}
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}
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